update

app.py

@@ -4,7 +4,7 @@ import pyterrier as pt
 pt.init()
 from pyterrier_gradio import Demo, MarkdownFile, interface, df2code, code2md, EX_Q
 
-retr = pt.TerrierRetrieve.from_dataset('msmarco_passage', 'terrier_stemmed')
+retr = pt.TerrierRetrieve.from_dataset('vaswani', 'terrier_stemmed')
 
 COLAB_NAME = 'pyterrier_retrieve.ipynb'
 COLAB_INSTALL = '''
@@ -17,13 +17,13 @@ def predict(input, _, wmodel, num_results, pipe_text):
   code = f'''import pandas as pd
 import pyterrier as pt ; pt.init()
 
-retr = pt.TerrierRetrieve.from_dataset('msmarco_passage', 'terrier_stemmed', wmodel={repr(wmodel)}, num_results={num_results})
+retr = pt.TerrierRetrieve.from_dataset('vaswani', 'terrier_stemmed', wmodel={repr(wmodel)}, num_results={num_results})
 '''
   pipeline = retr
   if pipe_text:
-    pipeline = pipeline >> pt.text.get_text(pt.get_dataset('irds:msmarco-passage'), 'text')
+    pipeline = pipeline >> pt.text.get_text(pt.get_dataset('irds:vaswani'), 'text')
     code += f'''
-pipeline = retr >> pt.text.get_text(pt.get_dataset('irds:msmarco-passage'), 'text')
+pipeline = retr >> pt.text.get_text(pt.get_dataset('irds:vaswani'), 'text')
 
 pipeline({df2code(input)})'''
   else:
@@ -37,11 +37,15 @@ interface(
   MarkdownFile('README.md'),
   Demo(
     predict,
-    {k: v for k, v in EX_Q.items() if k != 'antique/train'},
+    pd.DataFrame([
+      ['1', 'measurement of dielectric constant of liquids by the use of microwave techniques'],
+      ['2', 'mathematical analysis and design details of waveguide fed microwave radiations'],
+      ['3', 'use of digital computers in the design of band pass filters having given phase and attenuation characteristics'],
+    ], columns=['qid', 'query']),
     [
     gr.Dropdown(
-      choices=['msmarco-passage stemmed'],
-      value='msmarco-passage stemmed',
+      choices=['vaswani stemmed'],
+      value='vaswani stemmed',
       label='Index',
       interactive=False,
     ), gr.Dropdown(